/*
Detects SIFT features in two images and finds matches between them.

Copyright (C) 2006-2010  Rob Hess <hess@eecs.oregonstate.edu>

@version 1.1.2-20100521
*/

#include "sift.h"
#include "imgfeatures.h"
#include "kdtree.h"
#include "utils.h"
#include "xform.h"

#include "cvx_image\include\opencv\cv.h"
#include "cvx_image\include\opencv\cxcore.h"
#include "cvx_image\include\opencv\highgui.h"

#include <stdio.h>


/* the maximum number of keypoint NN candidates to check during BBF search */
#define KDTREE_BBF_MAX_NN_CHKS 200

/* threshold on squared ratio of distances between NN and 2nd NN */
#define NN_SQ_DIST_RATIO_THR 0.49

/******************************** Globals ************************************/

char img1_file[] = "beaver.png";
char img2_file[] = "beaver_xform.png";

/********************************** Main *************************************/


#if 0

int main( int argc, char** argv )
{
	IplImage* img1, * img2, * stacked;
	struct feature* feat1, * feat2, * feat;
	struct feature** nbrs;
	struct kd_node* kd_root;
	CvPoint pt1, pt2;
	double d0, d1;
	int n1, n2, k, i, m = 0;

	img1 = cvLoadImage( img1_file, 1 );
	if( ! img1 )
		fatal_error( "unable to load image from %s", img1_file );
	img2 = cvLoadImage( img2_file, 1 );
	if( ! img2 )
		fatal_error( "unable to load image from %s", img2_file );
	stacked = stack_imgs( img1, img2 );

	fprintf( stderr, "Finding features in %s...\n", img1_file );
	n1 = sift_features( img1, &feat1 );
	fprintf( stderr, "Finding features in %s...\n", img2_file );
	n2 = sift_features( img2, &feat2 );
	kd_root = kdtree_build( feat2, n2 );
	for( i = 0; i < n1; i++ )
	{
		feat = feat1 + i;
		k = kdtree_bbf_knn( kd_root, feat, 2, &nbrs, KDTREE_BBF_MAX_NN_CHKS );
		if( k == 2 )
		{
			d0 = descr_dist_sq( feat, nbrs[0] );
			d1 = descr_dist_sq( feat, nbrs[1] );
			if( d0 < d1 * NN_SQ_DIST_RATIO_THR )
			{
				pt1 = cvPoint( cvRound( feat->x ), cvRound( feat->y ) );
				pt2 = cvPoint( cvRound( nbrs[0]->x ), cvRound( nbrs[0]->y ) );
				pt2.y += img1->height;
				cvLine( stacked, pt1, pt2, CV_RGB(255,0,255), 1, 8, 0 );
				m++;
				feat1[i].fwd_match = nbrs[0];
			}
		}
		free( nbrs );
	}

	fprintf( stderr, "Found %d total matches\n", m );
	cvNamedWindow( "Matches", 1 );
	cvShowImage( "Matches", stacked );
	


	/* 
	UNCOMMENT BELOW TO SEE HOW RANSAC FUNCTION WORKS

	Note that this line above:

	feat1[i].fwd_match = nbrs[0];

	is important for the RANSAC function to work.
	*/
	
	{
		CvMat* H;
		H = ransac_xform( feat1, n1, FEATURE_FWD_MATCH, lsq_homog, 4, 0.01,
			homog_xfer_err, 3.0, NULL, NULL );
		if( H )
		{
			IplImage* xformed;
			xformed = cvCreateImage( cvGetSize( img2 ), IPL_DEPTH_8U, 3 );
			cvWarpPerspective( img1, xformed, H, 
				CV_INTER_LINEAR + CV_WARP_FILL_OUTLIERS,
				cvScalarAll( 0 ) );
			cvNamedWindow( "Xformed", 1 );
			cvShowImage( "Xformed", xformed );
			cvWaitKey( 0 );
			cvReleaseImage( &xformed );
			cvReleaseMat( &H );
		}
	}
	

	cvReleaseImage( &stacked );
	cvReleaseImage( &img1 );
	cvReleaseImage( &img2 );
	kdtree_release( kd_root );
	free( feat1 );
	free( feat2 );
	cvWaitKey( 0 );
	return 0;
}

#endif